Gavin’s TED talk – climate model sensitivity training

Love him or hate him, it is worthwhile to understand where he is coming from, so I present this video: The emergent patterns of climate change

According to TED:

You can’t understand climate change in pieces, says climate scientist Gavin Schmidt. It’s the whole, or it’s nothing. In this illuminating talk, he explains how he studies the big picture of climate change with mesmerizing models that illustrate the endlessly complex interactions of small-scale environmental events.

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” We know what happened over the 20th century. Right? We know that it’s gotten warmer. We know where it’s gotten warmer. And if you ask the models why did that happen, and you say, okay, well, yes, basically it’s because of the carbon dioxide we put into the atmosphere. We have a very good match up until the present day. ”

He describes the climate model as scaling of components of 14 orders of magnitude. From the microscopic seeds of the clouds to the whole of the planet. He does not mention the sun. For me, his credibility is already lost at 1:32.

Here’s a tip to all the CAGW computer modelers,
Why don’t you wait until your model is proven to work (AKA Release Candidate) BEFORE you release it into cyberspace? Or clearly label it as Pre-Alpha (might work sometime in the future – or not)?

Dear Gavin, unless you are carrying the error range of every number you feed into your model all the way through every calculation and out into the result, what’s coming out is not skillful, it’s fecal.

The climate has been warming slightly since the end of the little ice age with some ups and downs along the way, There has been no warming these last 17 years. The models can’t predict a damn thing. Gavin lied. Does he really believe what he is saying?

‘he explains how he studies the big picture of climate change with mesmerizing models ‘

Like a rabbit staring into headlights, well that does explain why he leaves his common sense and any scientific ability he has behind him, his ‘mesmerized by the models ‘ so simply unable to ask any questions of what they tell him .

Please repeat and re-repeat, Climate is a chaotic system, chaotic system cannot be modeled. Again I will point out private financial companies once attempt to “model” the stock market, to predict it direction to make money, they found out rather rapidly it did not work. When private money is at risk, modeling was put into the ash heap of history. Note to Gavin quit wasting taxpayer money.

Sorry, but I’m gonna call [snip] on that. Trying to say models in the 70’s suddenly ‘come good’ and then later, reflect the real world obs – is utter Bulldust. For one thing the models are trained on that recent data!
He announces the scale of the problem really well in the initial minutes – then proceeds to demonstrate how computer models can wipe out that scale problem over a few decades! ROFL – I don’t [snip] think so………
Sorry Anthony – but this isn’t worth squat in my humble opinion…….

How can he say the models are skillful? In what sense? They don’t predict the short term accurately, the medium term accurately, and so far they haven’t predicted the long term accurately (always running too hot over since their inception). I don’t think they can even hind-cast the past accurately.

I don’t know how he can stand there and say the the models are skillful. That just completely false.

The climate is very complex, very many factors to consider. We can and do write millions of lines of code for our models. Our models are so good we can not tell you accurately what the weather will be next week, much less tomorrow. But trust us, we know what will happen a 100 years for now.

If you look at the three global graphics at the end, the “do nothing, do something, do a lot” options… I sure as hell hope those computer models are wrong, because I think almost certainly mankind will choose the first option and do nothing.

I think it is good and right to post such videos here. The fact that we can all see the gaping flaws in Gavin’s arguments doesn’t matter. What does matter is that we can get a glimpse of what he is about, and formulate strong responses to his arguments. That is the task that lies ahead – we shouldn’t waste too much time patting ourselves on the back and saying “I told you so!”

“Emergent” hmm where have I heard this before. Oh yeah, Willis’s ’emergent phenomena’ that serve as a governor on climate overheating. I and others have stated before that something as good as Willis’s emergent phenomena and other climate findings won’t be out there long before they begin to be stolen. They are just too good. Okay, Gav has only used the word emergent, half of the idea but that’s a start.

Ya see, it will be stolen by the classic method of finding another word for phenomena. Remember the poetic “Continental Drift”? After vilifying Alfred Wegener for 40 years, for describing it in 1912, it was re-born as plate tectonics (sounds dental mechanic) in the 1950s to much acclaim by Alfred’s tormentors. I know the latter came with a solid explanation and I know there will be someone here belonging to the geological fraternity that will dump on Alfred Wegener again. He’s a bit like the MWP and the LIA that so much effort has been made by the Team to bury. We don’t do this to Eratosthenes whose speculation that matter was made up of atoms with no hooks for air, little hooks for liquids and lots of hooks for solids, probably because there were no established philopsophers painting themselves into a corner by angry dismissal on the subject.

At the end of the day, we are talking about what we can reasonably expect and how we either mitigate or adapt. We are already adapted for principal effects. Ironically, the skeptics, likened to the creationists in lieu of addressing their arguments, are in line with the Theory of Evolution and the Alarmists simply are not. As with experimental design, data collection, data analysis and interpretation, they lack understanding in a profound way.

The absolute best predictor of future performance, especially in the absence of compelling evidence to the contrary, is past performance. We have a record of past performance hard-coded into our genes. Our genetic adaptations to climate tell us that fairly different climates have existed in the past and we have adaptations both sides, hot and cold that reflect that fact.

I want to see solid replicated data collection with sound analysis, interpretation and argument. I have seen nothing approaching this and it has been many years and billions of dollars during which planet earth has been running the live experiment and modelers have run model versions of the experiment and the model versions do not match experimental data available by looking out your window.

I have to write a policy statement on global warming that will be used in political debate and with luck that may actually inform public policy. I will watch the comments here and if somebody can point me to sound data and genuine scientific argument that supports either side of this debate, I would be obliged.

I was pretty certain that any evidence I trusted supported a clear argument against the traditional Global Warming narrative. However, I was looking at everything through the lens of a skeptic. That is fine for your drinking buddies, but not so (for me) as a foundation for a defensible political policy on ‘Global Warming’ (framed in the context of ‘Environmental Stewardship’). When I look for good stuff, I find nothing anywhere that I can attribute back to a source I am comfortable with.

I am a fan of Wattsupwiththat and ClimateAudit and JoanneNova. However, these are sources with clear biases. The bias are, in my opinion, honestly come by and I share them in many cases, but as a matter of public policy I would like to point to specific things that are a bit less a part of the heated debate. I would like to create a sober sensible public policy that is above reproach as far as its scientific underpinnings; one that steers a manageable public course through a contentious issue where both extreme sides are prone to hyperbole.

I did a BSc back when they were still teaching science reasonably. My kids are receiving Catastrophic Anthropogenic Global Warming theory as something of a religious orthodoxy; teaching them both bad science and that bad science is science. Neither are good.

What I would really like to see is things like the multi-billion year CO2 profile data or some attribution for the graphs you see where CO2 obviously is being consumed out of existence by plant life and we are near the bottom.

I cannot find a reasonable trove of simple csv or tab delimited files of true raw data. The ‘value added’ stuff is suspect and therefore unacceptable when the analysis itself is under dispute. Particularly aggravating is that people who should have known better after graduating high-school use such patently biased methods of data collection that the whole data set is useless.

If this is settled science, where on earth is all the data?

Who is an honest broker? The nearest I seem to be able to find with any prominence is Judith Curry, but she is really still a ‘Climate Scientist’, all of whom have a vested interest in keeping their funding afloat. She seems to think that it is worthwhile public policy to fund continued massive research to be able to predict the Climate. As a matter of public policy we need to make hard decisions as to what is funded and what is not.

Clearly, something is horribly amiss with Climate Science and the continued prevailing Global Warming narrative. How do I express this plainly by pointing to sound research?

It is depressing that scientists as a community have not risen up and just put a bullet through the head of the CAGW zombie. It means, at this point, that they are either at least slightly unethical, incompetent, dishonest or both. A distant possibility is that they have evidence I have not. Where is it?

Gavin says
There’s a great phrase that Sherwood Rowland, who won the Nobel Prize for the chemistry that led to ozone depletion, when he was accepting his Nobel Prize, he asked this question: “What is the use of having developed a science well enough to make predictions if, in the end, all we’re willing to do is stand around and wait for them to come true?” The models are skillful, but what we do with the information from those models is totally up to you.

Henry says
what hogwash
what a load of rubbish
the ozone depletion was a natural process, mostly and the fact that it is now increasing is natural as well.
In fact, the increase in ozone (and others) at the TOA is what is causing the current cooling

So that was a red herring
The CO2 is not only a red herring, it is a green herring as well. More of it is better.

That was so sneaky. Gavin lists a great many “skillful” data sets and right in the middle “20th century multi-decadal trends.” The 20th Century data -as presented/reported- is highly suspect having been massaged beyond reliable.

The establishment scientists need take on board the fact that the Modeling technique is inherently useless for climate forecasting because models with such a large number of variables simply cannot be computed or indeed even initialized with sufficient precision and accuracy.
Take the time to watch –
The IPCC itself has been quite open about this and in practice the modelers have known for some time that their models have no skill in forecasting and have indeed said so in the WG1 reports. The IPCC AR4 WG1 science section actually acknowledges this fact. Section IPCC AR4 WG1 8.6 deals with forcings, feedbacks and climate sensitivity. The conclusions are in section 8.6.4 which deals with the reliability of the projections. It concludes:
“Moreover it is not yet clear which tests are critical for constraining the future projections, consequently a set of model metrics that might be used to narrow the range of plausible climate change feedbacks and climate sensitivity has yet to be developed”
What could be clearer. The IPCC in 2007 said that we don’t even know what metrics to put into the models to test their reliability.- i.e. we don’t know what future temperatures will be and we can’t calculate the climate sensitivity to CO2.This also begs a further question of what erroneous assumptions (e.g. that CO2 is the main climate driver) went into the “plausible” models to be tested anyway. This means that the successive SPM uncertainty estimates take no account of the structural uncertainties in the models and that almost the entire the range of model outputs may well lay outside the range of the real world future climate variability.
The key factor in making CO2 emission control policy is the climate sensitivity to CO2 . By AR5 – WG1 the IPCC is saying: (Section 9.7.3.3)
“The assessed literature suggests that the range of climate sensitivities and transient responses covered by CMIP3/5 cannot be narrowed significantly by constraining the models with observations of the mean climate and variability, consistent with the difficulty of constraining the cloud feedbacks from observations ”
In plain English this means that they have no idea what the climate sensitivity is and that therefore that the politicians have no empirical scientific basis for their economically destructive climate and energy policies.
In summary the projections of the IPCC – Met office models and all the impact studies which derive from them are based on specifically structurally flawed and inherently useless models. They deserve no place in any serious discussion of future climate trends and represent an enormous waste of time and money. As a basis for public policy their forecasts are grossly in error and therefore worse than useless
The entire IPCC output falls into the not even wrong category and provides no basis for serious discussion yet most anti alarmist bloggers and almost all the MSM pundits continue to refer to the IPCC forecasts as though they had some connection to the real world.
A new forecasting method must be used. For forecasts of the probable coming cooling based on the 60 and 1000 year quasi-periodicities in the temperature data and the neutron count and the 10 Be record as the best proxy for solar activity see several posts over the last two years athttp://climatesense-norpag.blogspot.com

Since the hot, plasticky place called earth is largely unvisited except for what’s on top; since the hydrosphere, the asthensophere, core etc are still pretty mysterious, as are most possible climatic influences beyond earth…isn’t it a bit premature and even impertinent to talk of “climate science”? Can’t we sex it all down a bit? Kind of worrying that volcanism is underfunded while these trashy non-Kardashian models are determining the West’s economic and industrial future. Those whirlygigs and solar panels are going to look mighty comical in the event of some natural cooling or a major series of basaltic eruption like Laki. Climate science? If only.

When I read stuff like this on various blogs I tend to view people like Gavin Schmidt with more disdain. It is his kind of ilk that has people saying this.

“Direct observations find that CO2 is rising sharply due to human activity. Satellite and surface measurements find less energy is escaping to space at CO2 absorption wavelengths. Ocean and surface temperature measurements find the planet continues to accumulate heat. This gives a line of empirical evidence that human CO2 emissions are causing global warming.”

With link to skepticalscience.
Alarmists are certain there is a line of empirical evidence.

“Gerry Parker says:
May 3, 2014 at 12:12 pm
And despite these claims of model skill, they consistently over predict warming.”

#####################
Skill is not measured that way.

Here is how you measure skill.

In 1938 imagine two people were asked the following question.

How warm will it be in 2014.

One, a skeptic, said the climate is unknowable. My best prediction is the temperature will be unchanged.
This is a naive forecast.
The other a climate scientist using a model said: if we increase c02 athe current rate, temperature will be 1C warmer.

You then measure how much closer the the modelled answer is to the truth than the naive answer

The skeptic says ” I don’t know”, yet, you then pretend he knows by making a claim “of the same”.

No climatologist whatsoever makes this claim. Climate ALWAYS CHANGES, so you infer the fellow that knows this (by saying “I don’t know”) suddenly puts himself upside down and claim the climate doesn’t change!

Then, you make up a conclusion that those that pretend they know actually do – when, in fact, they are clueless.

Priest of all persuasion of religion held the same discourse: you can’t comprehend anything up until you get the big picture. The underlying message is “you’re just to imbecile to see the light”. Of course, they know the only light is the one shining on them, for power, fame and profit.

Exactly, Rob – he makes claims that “models display ‘closely’ reality” but they really do not – he shoves aside his own graphs that show how far his models are off – but to him, its “skillful” enough to make dire predictions.

mosher~ please detail the qualifications of your ‘skeptic.’ That, for starters. Then explain how the ‘climate scientist’ has a computer model, or ANY model, of the climate based upon 1938 understanding of the science.

Mosh, I do not share the kneejerk antagonism to “models” of many commenters, but the CA post to which you refer doesn’t exactly support your assertion: it indicates that GCMs with positive feedbacks have no “skill” in forecasting global temperature relative to a “naive” no-feedback log relationship of Callendar 1938. I think that it’s entirely reasonable to criticize models on that point. As you and I have discussed, it’s unfortunate that the modeling community have failed to fully map the parameter space and left low-to-no feedback largely as a terra incognita, a mapping failure that seems to originate from a kind of academic stubbornness in the modeling community – it’s hard to contemplate similar behavior from commercial organizations.

Gavin has found himself a new propaganda platform and dispenses them the same old climate fairy tale of global warming. There was no science in his talk, just inspirational messages about orders of magnitude and skillful models. I did find one useful tidbit of data, however, namely that climate models today have over a million lines of code. Now consider this: they have been refining their climate models for twenty four years since Hansen presented his first one in 1988. Despite having switched to supercomputers with huge memories their model predictions are no better than Hansen’s that was done on an IBM mainframe. If you take a look at a CMIP5 output using 44 individual predictions (or “projections” as they like to disguise them), not one of them is even close to the reality of the twenty-first century they pretend to project. It is time to admit that climate modeling simply does not work and close it down. Those 44 all have the alleged volcanic cooling for El Chichon and Pinatubo also built in but they don’t even get that right. Pinatubo eruption really was followed by cooling period thanks to a convenient La Nina that followed. But El Chichon was followed by an El Nino peak and yet their moronic code shows that one too as a cooling. The temperature break at the turn of the century introduces fourteen years of no-warming and that also is totally ignored by their software whose million lines of code direct it to predict warming there. Their entire enterprise of predicting the future climate is handicapped by having greenhouse warming built into their code. That is because Hansen announced in 1988 that he had observed the greenhouse effect. He was wrong but nobody checked his science and he has been getting away with it for all these years. What he did in 1988 was to show a rising temperature curve, from 1880 to 1988. Its peak in 1988, he said, was the warmest point within the last 100 years. According to him there was only a one percent chance that it could happen by accident. Hence, there was a 99 percent probability that the greenhouse effect had been detected. Only problem is that his 100 year greenhouse warming includes the non-greenhouse warming in the early century that started in 1910 and stopped in 1940. Radiation laws of physics demand that if you are going to start an enhanced greenhouse warming you must simultaneously increase the amount of greenhouse gas in the atmosphere. There was no increase of atmospheric carbon dioxide in 1910. Hence, the warming of 1910 cannot be greenhouse warming. It must be removed from Hansen’s 100 year warming.This lops off the last 60 years of it and leaves a see-saw temperature curve, consisting of 25 years of cooling and 23 years of warming, as a remnant of his 100 years of warming. You don’t have to be a rocket scientist to know that no way can this be used to prove the existence of the greenhouse effect.

A million lines of Fortran, the mind boggles. Glad to hear that the’re not using punched cards anymore, saved a lot of trees..

Why do I suspect that somewhere in that million lines, an actual skillful programmer has hidden a call to a random number generator. Seems to me that the problem with climate modelling is that there would be absolutely no way to tell short of waiting 100 years.

“The art of diplomacy is to say nothing so convincingly that nobody notices” (Isaac Asimov “Foundation”)
“you can’t chop it into one little bit”
“I am going to chop it into lots of little boxes”
“the climate has a scale of 14 magnitudes”
“climate models now have 4 orders of magnitude – we have 14 to go ” (sic) Maths?
“models are always wrong”
“our models are skilful”
“IT IS THE WHOLE OR NOTHING”
Well, since he is a few magnitudes short he certainly hasn’t the whole so therefore, by his own logic, he has nothing.
Again from “Foundation” “after eliminating meaningless statements, vague gibberish, useless qualifications – he had nothing left, everything cancelled out.”

In the few model results, such as air pressure beneath the ozone hole, that Schmidt claimed showed skill, there were significant differences to reality (even though he claimed they showed skill). If the models don’t exactly mimic reality, there is no chance that they will get any closer if left to run longer. The truth is, the model results were headed off in some other direction. The models show skill in mimicking the past because they were tweaked to do so, but none in predicting the future.
Schmidt illustrated the magnitude of the problem at the beginning of his talk. He should have stopped there and admitted that there is no way to duplicate the chaos and complexity of the climate in computer code. His conclusion was that we had better take drastic action to stop emissions of CO2 because his models, which we know have little skill, might be correct. He is a fool and hopes that the rest of us are fool enough to follow him.

Gavin discovers that climatology is a generalist discipline. What he must now acknowledge is it is being dismembered and misused by specialist who call themselves climate scientists. The adage about not seeing the forest for the trees comes to mind.

His lips are moving. Worse, his models are running. I agree with Steve Mc – all models are not crap. I’m prepared to believe though that all climate models are crap. I get a lot of help in that belief from the climate models and which is supported by observed phenomena.

You can’t understand climate change in pieces, says climate scientist Gavin Schmidt. It’s the whole, or it’s nothing. In this illuminating talk, he explains how he studies the big picture of climate change with mesmerizing models that illustrate the endlessly complex interactions of small-scale environmental events.

The models illustrate a fantasy world of make believe. Here is Gavin at an earlier time. Note the date and what he said in reply to a question. Karl Popper would have been proud, but maybe not today. Maybe he is no longer worried about the state of understanding.

Real Climate – December 2007

Daniel Klein asks at #57:
“OK, simply to clarify what I’ve heard from you.
(1) If 1998 is not exceeded in all global temperature indices by 2013, you’ll be worried about state of understanding
(2) In general, any year’s global temperature that is “on trend” should be exceeded within 5 years (when size of trend exceeds “weather noise”)
(3) Any ten-year period or more with no increasing trend in global average temperature is reason for worry about state of understandings
I am curious as to whether there are other simple variables that can be looked at unambiguously in terms of their behaviour over coming years that might allow for such explicit quantitative tests of understanding?”
————

[Response: 1) yes, 2) probably, I’d need to do some checking, 3) No. There is no iron rule of climate that says that any ten year period must have a positive trend. The expectation of any particular time period depends on the forcings that are going on. If there is a big volcanic event, then the expectation is that there will be a cooling, if GHGs are increasing, then we expect a warming etc. The point of any comparison is to compare the modelled expectation with reality – right now, the modelled expectation is for trends in the range of 0.2 to 0.3 deg/decade and so that’s the target. In any other period it depends on what the forcings are. – gavin]http://www.realclimate.org/index.php/archives/2007/12/a-barrier-to-understanding/

Now understand this from less than a year ago.

Abstract – August 2013
The Key Role of Heavy Precipitation Events in Climate Model Disagreements of Future Annual Precipitation Changes in California
Climate model simulations disagree on whether future precipitation will increase or decrease over California, which has impeded efforts to anticipate and adapt to human-induced climate change……..Between these conflicting tendencies, 12 projections show drier annual conditions by the 2060s and 13 show wetter. These results are obtained from 16 global general circulation models downscaled with different combinations of dynamical methods…http://dx.doi.org/10.1175/JCLI-D-12-00766.1

I’m a software developer, that is I actually write code and have for 35 years. Computer models in science DO NOT contribute to the data they only express a hypothesis. Computer models in science in NO WAY can be considered experiments because model do not do science.

Computer models in ENGINEERING are an entirely different thing, I think the science cAGW modeller is a very confused or deliberately misleading person when they portray climate models as science.

I hate the idiot, they’ve never made a prediction that works, they have managed to *somehow* make their models predict the past. Oh I wish I could get paid to predict the past whilst claiming skill. What an an absolute idiot – as we already knew

I’m sorry, but there is absolutely no defence for the rubbish spouted by Schmidt – and no mater how many times Mosh calls models good for other things (usually stuff with like, two (wow!), variables!) there is absofrigginglutely no way to model climate in anything like a realistic way – there are just too many variables and too many scenarios. One day, these muppets who think computers CAN do everything, will realise that they actually CAN’T and no amount of sales pitch will convince me otherwise.

Steve McIntyre: ” I do not share the kneejerk antagonism to “models” of many commenters”

To dismiss the “antagonism” as “kneejerk” is insulting to the many commenters whose knowledge of physics and numeric methods enables them to see clearly that the climate models could not possibly model the major climate determinants well enough to rule out everything but CO2 as the cause of most warming. The claim that the models can do so is an extraordinary claim that requires extraordinary proof.

The oceans, combined with oceanic/atmospheric oscillation cloud cover, especially over the tropics, have a FAR greater capacity for soaking up shortwave IR and keeping hold of it than atmospheric anthropogenic CO2 absorption capacity has in the spat out longwave IR spectrum. It is, at the very LEAST, just as likely that intrinsic natural variables, ones that have decades long oscillations, are the reason for the decadal energy imbalance Gavin speaks of. AND HE KNOWS IT! But he beats the CO2 drum because he has to sing whatever tune they give him for his dinner.

Perspective – Science – 31 May 2013What Are Climate Models Missing?
Bjorn Stevens1, Sandrine Bony2
Fifty years ago, Joseph Smagorinsky published a landmark paper (1) describing numerical experiments using the primitive equations (a set of fluid equations that describe global atmospheric flows). In so doing, he introduced what later became known as a General Circulation Model (GCM). GCMs have come to provide a compelling framework for coupling the atmospheric circulation to a great variety of processes. Although early GCMs could only consider a small subset of these processes, it was widely appreciated that a more comprehensive treatment was necessary to adequately represent the drivers of the circulation. But how comprehensive this treatment must be was unclear and, as Smagorinsky realized (2), could only be determined through numerical experimentation. These types of experiments have since shown that an adequate description of basic processes like cloud formation, moist convection, and mixing is what climate models miss most.http://www.sciencemag.org/content/340/6136/1053.summary

And all the time new papers come out questioning the models. This is an exercise in failure. The more they fail the more money they want to continue failure. The UK Met Office’s latest computers are a prime example of failure. 12 out of 13 over projected warming. GIGO.

Steve Mosher says:
“In 1938 imagine two people were asked the following question: How warm will it be in 2014?
One, a skeptic, said… my best prediction is the temperature will be unchanged. This is a naive forecast.
The other a climate scientist using a model said: if we increase c02 athe current rate, temperature will be 1C warmer.
You then measure how much closer the modelled answer is to the truth than the naive answer.”

Steve: In 1930 imagine two people were asked the following question: How warm will it be in 1979?
Now how much closer is the modelled answer to the truth than the naive answer?

“Even though it was concealed from those who constructed the models, the purpose of climate models was to provide the power of metaphor to political rhetoric:

…climate change models are a form of “seduction”…advocates of the models…recruit possible supporters, and then keep them on board when the inadequacy of the models becomes apparent. This is what is understood as “seduction”; but it should be observed that the process may well be directed even more to the modelers themselves, to maintain their own sense of worth in the face of disillusioning experience.

…but if they are not predictors, then what on earth are they? The models can be rescued only by being explained as having a metaphorical function, designed to teach us about ourselves and our perspectives under the guise of describing or predicting the future states of the planet…A general recognition of models as metaphors will not come easily. As metaphors, computer models are too subtle…for easy detection. And those who created them may well have been prevented…from being aware of their essential character.”

The “anthropogenic” models are not really models. They use pretty good general circulation models that they then tweak and twerp adding a predetermined warming rate calculation along with a sprinkling of aerosoles to mimic the training period and then let them run.

So I am of the same opinion as McIntyre. General circulation models are a work in progress and well worth the investment. It is what biased researchers do to them that reeks of rent seeking behavior.

Steven Mosher says:
May 3, 2014 at 1:50 pm
……
Skill is not measured that way.
Here is how you measure skill.
In 1938 imagine two people were asked the following question.
How warm will it be in 2014……..

Could your co2 guy then explain the subsequent cooling? If yes please explain in full.

IanH says: “… they’ve never made a prediction that works, they have managed to *somehow* make their models predict the past. Oh I wish I could get paid to predict the past whilst claiming skill. …”

Exactly! They can predict the past and they can “adjust” the data sets, but they just can’t make their models predict the future. The hypothesis that CO2 will lead to catastrophic global warming is hogwash.

Most striking to me is Gavin’s presentation suggests that CO2 attribution studies are most likely very wrong. CO2 attribution studies argue that because “skillful” models can not explain current climate without adding CO2, then current climate must be due to added CO2. But by his own evidence the models fail miserably to capture the climate before the 1970s.

Stop his fast paced animation comparing observation and model results anytime from 1892 to 1970 and the patterns of warming and cooling are not in agreement. There is no skill. They have simply tweaked the models to match trends from the late 70s to now. Most likely, just as the ancient modelers added imaginary epicycles to match contradictory observations to advocate and protect their intellectual status, Gavin et al have simply added climate epicycles but failed to model global climate from 1900 to 1970.

@SteveMosher,
Science doesn’t happen in a vacuum. It does have a history. And in 1938, atmospheric scientists said quite a bit – much of it was all over the place. Fast forward to the 1970s (the decade when scientists worldwide first began to accurately model the atmospheric as a whole). And many of them in places like NOAA and NASA projected cooling. Of course, they didn’t have the knowledge we have today. Yes, they knew about the Walker and Hadley Cells; they knew about various atmospheric pollutants, aereols, not to mention Greenhouse gases. Yet, there was no definitive understanding of the one of the globe’s primary atmospheric/oceanic oscillations -ENSO.

But, even with that knowledge, our main climate scientists insisted and continue to insist that ENSO and other oscillations are secondary to Greenhouse gases. Yet, their projections are not only off, but terribly so. Yes, they’ve to the trends correct. But, in weather forecasting that is just called persistence. You guys are just using persistence and then declaring victory. Based upon your model projections, it is fair to say that your understanding of our climate is poor. Someone has to write the code, and the code is just a reflection of your understanding.

Dr Norman Page says “The establishment scientists need take on board the fact that the Modeling technique is inherently useless for climate forecasting because models with such a large number of variables simply cannot be computed or indeed even initialized with sufficient precision and accuracy. “.

Dr Norman Page is absolutely correct. Climate is what happens over decades, centuries, millenia, and more. Think Ice ages. Think Al Gore’s famous graph showing peaks in temperature and CO2 about every 150,000 years. Think warming and cooling periods like the Roman and Medieval Warm Periods and the Little Ice Age. Think warm decades like the 1930s and cool decades like the 1960s.

There is nothing – absolutely nothing – in the climate models that explain any of the past climate events or predict the next one. The reason is that they work on the minutiae of weather. It is absolutely impossible to model a decadal or longer event whose cause is unknown by dividing the globe and time into small parcels and then trying to follow the short term impact of each parcel on its neighbours in space and time. Those models are not climate models, they are weather models (and not very good weather models at that). Even the best weather models cannot successfully predict more than a few days ahead.

Ok then – let me ask a really simple question – when you are in your garden, say, burning leaves, or a having a BBQ, how many times has the wind shifted? Was this predictable? Why not? Bear in mind, this is on a micro scale – i.e. your garden! – Now try and upscale this and imagine how multiplied any errors become. Sorry, but no GCM can model even the basic wind patterns as far as I am concerned – and I think the UK Metoffice proves this on a regular basis with it’s rubbish forecasting!. I’m not saying that GCM’s can’t have a use – but simply that computer modelling, as advertised, is not ANYTHING like it is hyped up to be – and WORSE – it is presented as being RELIABLE! All of which is false!
best regards, Kev

FUTURE temperature projection skill is all that matters and since the IPCC’s first report in 1990 they have failed time and again V OBSERVATIONS. Telling me how well they simulate anything in the past is garbage. They know what to tweak and voila!

It was a classic case of experts who find that within the areas where they have detailed knowledge of the AGW issue they find the evidence wobbly and problematic, but assume it’s solid everywhere else.

Gavin’s ‘big problem’ is that the central question to his view of climate change is HOW MUCH of a contribution are humans making to global warming.
As Gavin has noted on Real Climate, his answer to his central question of climate sensitivity has always been based on the response of the climate system to forcing that has occurred since the Last Glacial Maximum, some 20,000 years ago.
The question Gavin really wants to answer, therefore, is the physics of the interglacial cycles, or climate change over periods of > 20,000 years.
Yet, in his talk all he talks about is cloud resolution and ice crystals, mini tornados, dust from the Sahara, etc. All the stuff which has absolutely nothing to do with reducing the uncertainty of his central question.
It’s quite possible Gavin’s view of climate change is right, and also possible that we may never know how to predict “glacial maximum events”. Ignorance of the physics is not reason for inaction.
There is however, one good reason for inaction, and that is a cohort of over confident scientists playing down uncertainty, or even worse, not even talking about the real reasons why they could be wrong!
Gavin is a modern-day pseudo.

Nature Climate Change | Letter – 7 April 2013Retrospective prediction of the global warming slowdown in the past decade
Virginie Guemas et al
Despite a sustained production of anthropogenic greenhouse gases, the Earth’s mean near-surface temperature paused its rise during the 2000–2010 period1. To explain such a pause, an increase in ocean heat uptake below the superficial ocean layer2, 3 has been proposed to overcompensate for the Earth’s heat storage. Contributions have also been suggested from the deep prolonged solar minimum4, the stratospheric water vapour5, the stratospheric6 and tropospheric aerosols7. However, a robust attribution of this warming slowdown has not been achievable up to now. Here we show successful retrospective predictions of this warming slowdown up to 5 years ahead, the analysis of which allows us to attribute the onset of this slowdown to an increase in ocean heat uptake. Sensitivity experiments accounting only for the external radiative forcings do not reproduce the slowdown. The top-of-atmosphere net energy input remained in the [0.5–1] W m−2 interval during the past decade, which is successfully captured by our predictions. Most of this excess energy was absorbed in the top 700 m of the ocean at the onset of the warming pause, 65% of it in the tropical Pacific and Atlantic oceans. Our results hence point at the key role of the ocean heat uptake in the recent warming slowdown. The ability to predict retrospectively this slowdown not only strengthens our confidence in the robustness of our climate models, but also enhances the socio-economic relevance of operational decadal climate predictions.http://www.nature.com/nclimate/journal/v3/n7/full/nclimate1863.html

Did you see that?“The ability to predict retrospectively this slowdown not only strengthens our confidence in the robustness of our climate models”.
GIGO really does apply. Now I know why the computer guys came out with such a term. It all makes so much sense now.

Kev, you bring to the table an inappropriate example (possibly from a misunderstanding?) of the purpose and output of general circulation models. They cannot predict or model the direction or strength of wind at ground level on a scale tiny enough to capture my garden. That is why their title includes the word “General”.

First, if the same question had been asked only 17 years ago the naive answer would have been correct.

Second, long term trends were well known even back in 1939. It was recognized that the earth was coming out of the Little Ice Age. That the earth was warming was evident and because the earth had not yet warmed to the level of the Medieval Warm Period more warming would be indicated. A truly naive predictor exists only in your imagination.

Third, “skillful” is a sound byte word. It means “having or showing great skill”. Skill is “the ability to do something well”.So something that is skillful has shown the ability to do something well.

i suggest you compare the predictions made in the past using climate models and the real world events that occurred. They don’t match. Climate models are not skillful.

Abstract – 3 June 2013Historical Antarctic mean sea ice area, sea ice trends, and winds in CMIP5 simulations
[1] In contrast to Arctic sea ice, average Antarctic sea ice area is not retreating but has slowly increased since satellite measurements began in 1979. While most climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) archive simulate a decrease in Antarctic sea ice area over the recent past, whether these models can be dismissed as being wrong depends on more than just the sign of change compared to observations. We show that internal sea ice variability is large in the Antarctic region, and both the observed and modeled trends may represent natural variations along with external forcing. While several models show a negative trend, only a few of them actually show a trend that is significant compared to their internal variability on the time scales of available observational data. Furthermore, the ability of the models to simulate the mean state of sea ice is also important. The representations of Antarctic sea ice in CMIP5 models have not improved compared to CMIP3 and show an unrealistic spread in the mean state that may influence future sea ice behavior. Finally, Antarctic climate and sea ice area will be affected not only by ocean and air temperature changes but also by changes in the winds. The majority of the CMIP5 models simulate a shift that is too weak compared to observations. Thus, this study identifies several foci for consideration in evaluating and improving the modeling of climate and climate change in the Antarctic region.http://onlinelibrary.wiley.com/doi/10.1002/jgrd.50443/abstract

The IPCC in AR5 has acknowledged this failure. Are we not wasting our time with the climate models? They are not fit for the purpose as shown since the IPCC’s first report. They are a load of dog’s dropping. Spend the money on the poor and homeless instead of rent seeking tricksters trying to sell us new electrickery.

Mosher,
Do you get paid in cold hard cash for advocating for the failed climate computer models. THEY HAVE FAILED! If these climate models were adapted and relied on by 10,000 investors in stocks then the fund management company would have gone bust. You can’t run an investment company since 1990 with a record of guaranteed failure. Yet this is what you are trying to sell me. I am not buying your stocks.

A lesson on humility and the ordinary man’s acute sense of a scam.

BBC – 19 April 2013The student who caught out the profs
This week, economists have been astonished to find that a famous academic paper often used to make the case for austerity cuts contains major errors. Another surprise is that the mistakes, by two eminent Harvard professors, were spotted by a student.http://www.bbc.co.uk/news/magazine-22223190

BBC – 10 January 2014
“Only days before the 1929 stock market crash, one of the best known economists of the time, Professor Irving Fisher of Yale University, announced that “stock prices have reached what looks like a permanently high plateau”. Even after the crash occurred, Fisher insisted it was only a market correction that would soon be over. Losing most of his own fortune, the distinguished economist was as deluded as nearly everyone else. In case you’re wondering who anticipated the crash, two who did were the mobster Al Capone, who described the stock market in the boom years as a racket, and Charlie Chaplin, who unsuccessfully pleaded with his friend, the songwriter Irving Berlin, to sell out the day before the market collapsed.”http://www.bbc.co.uk/news/magazine-25680144

Ultimately the video is showmanship, pure showmanship to “sell” the climate model story. He ticks off on a bunch of successes modelling phenomena that occur at a large scale and the graphics coming from this sort of stuff is captivating and, when the numbers are good, compelling and inspiring. Trouble is for the past couple of decades the temperature numbers have not been good compared to the measurements, the measurements have a bit of a question mark over them ( as having been tweaked upwards) and it is well understood that the evaporo-transpiration system, formation of cumulus clouds, tropical and subtropical storm formation in particular happen at a relatively small, virtually local scale. This is true of most natural evaporation/precipitation phenomena that rely on extremely localised initiation to get going and at that point the models need fudge factors.

The models can handle the physics of most of the phenomena with reasonable and useful accuracy but not all. In other fields other methods are resorted to at this point because it is known that fudge factors do not deliver realistic let alone reliable results. It requires an arrogance driven by influences on the human condition other than objective, scientific enquiry for its own sake to present these models as a ‘one stop shop’ for your climate reality. It seems to me that at this point in time we are in a search for honesty and credibility much more than scientific knowledge on this subject.

Mr Schmidt’s talk was generally informative and one would only have to change the last few minutes to give a proper state of the science to a lay audience but ultimately, without the necessary caveats and admissions of work still to be done, it misrepresents the models and their accuracy and simply seeks to blind the audience with “science” and mere spectacle.

…it’s unfortunate that the modeling community have failed to fully map the parameter space and left low-to-no feedback largely as a terra incognita, a mapping failure that seems to originate from a kind of academic stubbornness in the modeling community…

Steve, do I understand you correctly? You seem to me to be saying that modelers generally don’t investigate low to no feedback because of their parameter choices. I wasn’t under the impression that this was a parameter, I thought the feedbacks in the models arose somehow from the algorithm being iteratively applied.
I’d love to hear more about this. Thanks all.

Steven Mosher says:
May 3, 2014 at 1:50 pmSkill is not measured that way.

Rubbish. All of it.

Skill is not measured by the artifice of setting up a straw man argument and then knocking it down.

Let’s try a realistic perspective instead. You can call it ‘skeptical’, if you like:
“The earth has been warming in fits and starts for approximately the last 11,700 years, allowing mile thick glaciers to slowly melt and recede world wide. Realizing atmospheric CO2 gas concentrations in the range of 250 – 1000ppm has only a tertiary influence on ‘global warming’, we can anticipate that the earth’s atmosphere will continue to warm in fits and starts until the true drivers of this Holocene interglacial warming (natural drivers as yet undetermined with certainty) wane and the planet again starts the inevitable slide into another massive 100,000 year long glaciation period again. This is a well established natural cycle which atmospheric CO2 has little ability to prevent, more is the pity! Would that it could, for it will be woe unto mankind, when the cold embrace of glaciation again asserts itself on the vast areas that are currently inhabited by a panoply of all God’s flora and fauna. ”

That is the ‘skeptics’ prediction, based on real observations of our planets natural cycles.

Nevermind my question, AR4 WGI 8.6.2.3 looks like it talks about this. Different models exhibit different feedbacks, water vapor and lapse rate and cloud feedback and so on.
What I didn’t realize (but probably should have) is that modelers haven’t explored low feedback parameters. That’s just sad.

Steve McIntyre said:
“it’s unfortunate that the modeling community have failed to fully map the parameter space and left low-to-no feedback largely as a terra incognita.”
When skeptics, convinced that H2O feedback is terra incognita, and that the climate sensitivity is low, look at the scenarios painted by the successive IPCC model runs, we see the general problem and conclude the models are crap.

May 3, 2014 at 1:50 pm
=================================
Couldn’t a similar argument made about speaking to a Viking in Greenland in 1033, with regards to the temperature in 1700 and be “not skillful” (layman here – go easy please)

Thanks to our host for posting this, it is important to understand where guys like Dr. Schmidt are coming from.

What is the use of having developed a science well enough to make predictions if, in the end, all we’re willing to do is stand around and wait for them to come true?” The models are skillful, but what we do with the information from those models is totally up to you.

We can quibble about what the word skill means, but I don’t think it matters here.
This statement of Dr. Schmidt is so blatantly misleading that to me it’s as inexcusable as an outright lie. What’s the use of having developed a science well enough to make predictions that haven’t happened if, in the end, all we’re willing to do is stand around and pretend the science is OK even though the projections have not matched observations would be a much better question IMHO.

The paid-for “Ted Talk” (as all Ted Talks are now) starts with a fake “crowd-applause-soundtrack” and then ends with the same fake “crown-applause-track”.

It would have been far more entertaining and far more accurate if there was also a “laugh-track” along with it after every sentence made by Gavin. Situation comedy is what it was.

His models are comedic. His talk needs a laugh-track (like when he said climate models haven’t move onto C programming yet – C was invented in 1969 – Fortran in 1959).

If you like your global warming, you like your climate models and you like your Gavin. If you like your evidence, then you do not get to work on climate science at a University or an Institute, If you like your evidence, you get fired. If you like your fake applause-track, you get promoted.

We certainly do have skilful models predicting weather and those excellent visual representations of models runs are displaying that. Frankly the BOM (in Australia) does an excellent job of predicting weather, several days in advance now.

What we dont have is skill in perturbing the system into unknown and previously unseen states because our understanding of the interactions is based on known combinations and our understanding on interactions with different states is obviously poor.

Skill with Weather simulations != Skill with Climate simulations

Gavin is trying to convince himself as much as anyone in that video. And in typical “team fashion” he oversold the models without acknowledging their weakness in anything other than an “it’ll be alright in the end, meanwhile trust us now” way.

TED is relentless Warmist and will not countenance skeptical contributions.
Therefore I will not watch TED stuff…even though I may be missing out on an opportunity to pillory Gavin as he writhes and wriggles and tries to claim that he’s right even though he is so clearly and spectacularly wrong!

I noticed the “skillful” model graphic animations stopped at the end of the 20th century.

Not so “skillful” since then, are they?

I still remember the video clip posted here a while ago, when Gavin appeared on a news program and slithered off the stage before (I believe) Dr. Spencer (or Christie) joined the panel. The man is a coward and a liar. It’s sad that people like him can a position a position of power and influence.

” We know what happened over the 20th century. Right? We know that it’s gotten warmer. We know where it’s gotten warmer. And if you ask the models why did that happen, and you say, okay, well, yes, basically it’s because of the carbon dioxide we put into the atmosphere. We have a very good match up until the present day. ”

That’s just it; we don’t know globally what happened over the entire 20th century. We only have half way decent global observations from the beginning of the satellite era.

Here’s the other thing, who still uses FORTRAN? I haven’t used FORTRAN since college. He might as well of said: trust us we’re on the cutting edge of science even though we’re 3 decades behind in technology.

I note you have presented talks by several proponents of Global Warming/Climate Change. However, you have not given an opportunity to present the other side of the issue to climate skeptics. There are several notable, peer reviewed climate experts who present the skeptical view. Among them are Richard Lindzen at MIT, Willie Soon at the Harvard Smithsonian Observatory, Judith Curry at Georgia Tech, Roy Spencer and John Christy at the University of Alabama and a long list of other Ph.D. experts. Please invite one or more of these experts to take the stage at a future conference. Balance of scientific opinion is important.

Regards,

John Coleman

I think if would be excellent if they heard from many of the rest of you.

I liked the orders of magnitude paradigm, a very useful way to illustrate the difficulty of the problem

Surprisingly, he used only 14, with the size of the earth as the upper bounds – somewhat surprising as he clearly (despite some comments upthread) acknowledged the influence of the sun. The 4 down 14 to go was simply the artifact of a live presentation.

I see some chuckles about Fortran, and can only assume people are doing serious modeling.

In a recent role with my company, I worked with a moderately sophisticated financial model. It was written in Fortran, because we had to model interest rates, inflation, and the interactions as they affect bond prices and yields, not to mention stochastic insurance loss projections. Fortran was used because it is a suitable language to do very heavy duty number-crunching. It makes a nice sound-bite to treat it as antiquated, but only to those who don’t really do heavy duty modeling. (Which is not to say it is always the best option – I’ve modeled some processes in APL, some others in Excel,, the choice depends on how much number crunching is needed. One can have a highly sophisticated model that doesn’t require a lot of number crunching, but models of the financial world and models of the climate need to do a lot of brute force calculations)

The problem isn’t fortran. The problem is implementing different bits of math outside of a high level architecture that ensures quality and allows for measures of confidence. I’ve worked on problems of less complexity, that required far more effort from the coding side to even get past the initial reviews at the pentagon.

Gavin Schmidt is a self proclaimed expert in his climate modelling field. To protect his own authority to make expert statements his questionable skill, is avoiding direct and public debate with scientists who challenge that expertise.

In a court of law, an expert must submit to probing cross examination to establish that they are what they claim to be, in the knowledge of the court and, before their evidence as an expert will be accepted.

While Gavin and many of his colleagues shrink from public debate with other sceptical scientists, they cannot expect to be taken seriously!

Untested authority statements in those circumstances should not be used in determining public policy outcomes, or used only under suitable caution.

And let me say this “pal review” and setup “pal debates” with fellow nodding puppets do not qualify as a public honest debate. Especially so when dealing with political policies and responses that will impact on the rights, wellbeing or, economic circumstances of others.

“The ability to predict retrospectively this slowdown not only strengthens our confidence in the robustness of our climate models”

It boggles the mind that someone could make the above statement and keep a straight face. ‘Retrospective prediction’ is a contradiction in terms. You can’t predict what has already happened. The fact that they can adjust the parameters that stand for lack of knowledge of how the underlying processes function (clouds, PDO, volcanism, etc) to mirror past events does not give me any confidence in the robustness of the models. That is a nonsense statement worthy of Lewis Caroll.

[b]Ocean Vents And Faulty Climate Models[/b]http://quadrant.org.au/opinion/doomed-planet/2014/05/ocean-vents-faulty-models/
[blockquote][i]It hardly needs to be said that climate modelling is a far-from-settled science, despite what its practitioners would have us believe. Just how flawed becomes even more apparent when you consider that massive heat sources on the ocean floor have been entirely omitted from the warmists’ calculations[/i][/blockquote]

Putty in their hands as a “man of vision” leads them over the intellectual precipice. I wonder how impressed his audience would have been had they known that what record there is of climate model accuracy is the result of furious, after-the-fact hind-casting.

Schmidt’s talk tells me more about Schmidt than it does about his presentation. He is either convinced about what he spouting or in a state where he is so deeply entrenched that he dares not backtrack, and has closed his mind about any conflicting data or flawed underpinning that renders the climate models as merely cartoons of reality.

His definition, or more correctly his believe, that the climate models display “skill” is laughable as is Mr Mosher’s ridiculous ‘illustrative example”.

Well, I don’t know the man, and this is the first I have seen of him. A lot of hand waving, and he quickly whisked away the abstract and the cement ; excuse me, that’s the concrete, not the cement.

Well he impressed on us just how much minutiae goes into these models. The live models running in video were stunning. So this impressed on me, just how much of the fine detail goes into the models.

That leads me to believe; or at least presume, that the real climate in real time, is being depicted by these models running, which means that there aren’t appreciable, or at least significant, delays between what the model predicts, and the actual occurrence of the result.

So how in the hell, is there virtually NO correspondence whatsoever, between just one important aspect of the climate; the “global average temperature anomaly” predicted by the model, and that actually measured by a multibillion dollar monitoring system of the real “GATA”.

So Gavin says, there’s 14 orders of magnitude to the range of this system, and they are modeling four orders of magnitude.

Which one are you modeling Gavin; and are they contiguous ??

So we saw micron sized aerosols, and we hear a lot about how important they are. So I’ll be generous, and say that scale is 100 microns; and that’s where they start. That’s their (h) in the equivalent to E = h nu.

So 10^4 x 100 microns, is 10^6 microns; roughly one meter. So that’s about from my front door to down the first step , or thereabouts.

Nope, that doesn’t work; not nearly global climate.

Earth’s circumference is 21,600 nautical miles (a mile a minute), so 10^-4 of that is 2.16 nautical miles x 1852 = holy cow; 4000.32 meters !

So if I’m happy with a one dimensional globe model, and four orders of magnitude, I need one “weather” station every 4 km, and maybe it can be about 0.32 meters square; about the size of one of those smaller boxes with the incandescent light bulb in it , to keep the snow off the thermometer.

Well that doesn’t work either; Dr. Hansen, is only putting one every 900 km or so.

And what if I want a two, or even a three dimensional climate model; well a two on curved space will do. Do we have that many thermometers on this planet.

Well Dr Roy, and Prof Christy have a time shared one that they loan around the world, so it seems to be almost everywhere

I’m really having a hard time trying to imagine which four orders of magnitude Gavin is modeling. I wonder if Peter Humbug, knows which ones ??

If I take for granted, that the climate models say the climate is changing rapidly; I didn’t hear one word from Gavin, about what exactly is going to happen, when the fat hits the shin, and all that model clay comes to pass.

I might believe he had a valid model for predicting the future when he can zero the model for whatever base time he chooses. Then run it backwards for 2000 years prior to his base time. If he matches what the weather actually was in that past period, then he has a chance of predicting to future. But I doubt that he understands why the magnetic poles are drifting, or why the poles flip and flip back, or how that effects the climate. Why do we keep having ice ages, and why do they start and end. The most his model can say is if things remain the same in the future as they were in the test period then this is what we think will happen. Unless something happens that we did not account for, or there is a Black Swan Event, like a super volcano, or an asteroid hit or an EMP even from the sun, or the poles reverse.

I thought it extremely interesting and would happily sit through a longer lecture by Dr Schmidt.

I may not agree with his conclusions but the talk certainly allows you to see where he is coming from. Note that he admits the models are “wrong” and should, can and hopefully will be improved. However he thinks that they are good enough for a “reasonable” projection of the future and that future improvements in the models will refine the projection but not fundamentally change it.

If you had a model that you thought gave a reasonable projection and the results of that projection gave you cause for concern, wouldn’t you speak loudly too? Dr Schmidt models climate and the results have convinced him that there are grounds for concern.

He spoke fairly from his point of view and that is the best that anyone can do.

I would like to hear more about “modeling”. (Really, aren’t these more realistically called SIMULATIONS? Aren’t these modelers striving to duplicate The Climate Matrix? Reality from a virtual world?)

I think Gavin’s talk had merit. The magnitudes of SCALE in BOTH time and size are extremely significant in simulating climate. Small scale events affect large scale events and vice versa. For example, cloud formation starts with microscopic (molecular?) particle behavior but clouds act on a global scale. How many orders of magnitude is that?

So these simulations with terabytes of information and code run on super computers with hundreds? of cores. And they strive to make the simulations ever more complex. Derived data is fed back into the simulation to derive more results. And how long does it take for a simulation to run at that level of complexity, even on a supercomputer? Is it really necessary? Perhaps not….. simple models are sometimes reflect reality just fine.

We certainly do have skilful models predicting weather and those excellent visual representations of models runs are displaying that. Frankly the BOM (in Australia) does an excellent job of predicting weather, several days in advance now.

Must be highly localised, Tim. Invariably i do better by sticking my head out of the window to check the cloud formation and the barometer … sometimes even watching what the ants are doing. But then, I’m an old yachtie. Have noticed over time that the BoM forecasts for Brisbane (Aust.) mostly run a degree-C or so hot.

We have dozens of models with different assumptions about the climate producing widely divergent results. Why can’t we just concentrate our efforts on having one good model? Climate science apparently can’t or certainly won’t express an opinion about the relative level of ‘skill’ among the many competing models.

The predictions (or substitute a weasel word) for global temperatures range from historical recovery rates from the Little Ice Age to something like three times that amount. The spread has not narrowed in twenty years and forecasts to date have failed.

But the science is settled and we are oh so gosh darn 95% certain that we have it right!

We are still in a situation where our knowledge is insufficient and climate models are not good enough. What we need is more basic research freely organized and driven by leading scientists without time pressure to deliver and only deliver when they believe the result is good and solid enough.

… Professor Lennart Bengtsson.

Professor Lennart Bengtsson has a long and distinguished international career in meteorology and climate research. He participated actively in the development of ECMWF (European Centre for Medium-Range Weather Forecasting) where he was Head of Research 1975-1981 and Director 1982-1990. In 1991-2000 he was Director of the Max Planck Institute for Meteorology in Hamburg. Since 2000 he has been professor at the University of Reading and from 2008 the Director of the International Space Science Institute in Bern, Switzerland.

Professor Bengtsson has received many awards including the German Environmental Reward, The Descartes Price by the EU and the IMI price from the World Meteorological Organisation (WMO). He is member of many academies and societies and is honorary member of the American Meteorological Society, the Royal Meteorological Society and European Geophysical Union. His research work covers some 225 publications in the field of meteorology and climatology. In recent years he has been involved with climate and energy policy issues at the Swedish Academy of Sciences.

John West asks “who still uses FORTRAN”. I do! I have also taken classes and/or programed in machine language, Assembler, BASIC, Pascal, Balgol, Ada, C, C++, C#, HTML, and Postscript. What language I use depends on the task at hand. FORTRAN is my favorite programming language. I can program FORTRAN in my sleep. At times I use shell scripts, but the rest have mostly fallen by the wayside. BTW my last job that involved programming ended in 1999.

David in Michigan says:
May 3, 2014 at 7:20 pm
I repeat, I’d like to hear more about these models.
—————————————————————————————-
I’d like to hear more about the assumptions wouldn’t you?
The main assumption that human CO2 is the main driver of temperature increase has not been convincing over the last 17 years and 9 months or responsible for those temp increases before the industrial revolution.

‘One, a skeptic, said the climate is unknowable. My best prediction is the temperature will be unchanged.

In 1938? Temperatures were still rising.There were no skeptics because nobody was saying it was CO2. Ask the same question in 1970 and Kenneth Watt proclaims at the first Earth Day:

“At the present rate of nitrogen build-up, it’s only a matter of time before light will be filtered out of the atmosphere and none of our land will be usable.”

I can actually remember the day and being rather skeptical of this claim. The physics was well enough known then that Kenneth should have know better. But there are some rather small NO absorption bands and there is always the possibility that some strange property will emerge.

If the 1938 question had been, “How warm will it be in 1970?”, the climate scientist’s answer would have been wrong, as wrong as Kenneth Watt.

So at the last glacial maximum a Homo habilis and a climate scientist are discussing the future and the climate scientist opines that if we don’t stop burning so many campfires the temperature will be 5 degrees warmer in 2014. Does the climate scientist show skill?

I guess it’s nothing then, because you can’t understand how any system works until you understand how the pieces work individually and how they interact with each other, and Climate Science doesn’t have all the pieces yet.

Some of this lecture was cleverly constructed. The variables that dictate weather, and climate for example pollution was thrown in. Well pollution poisons the air we breathe admittedly, and when the sun is cut off via clouds or dust, yes it does cool the climate, it doesn’t heat it up. He didn’t mention jet streams, but he did mention orbit. And cutting down large areas of rain forest, has proven that the transpiration from these areas do change the height of clouds in and around the region, so precipitation patterns move. Volcanoes yes can alter and cool the planet for a while.
China’s pollution, yes from coal surface burning fires. But CO2 increases decrease when the planet cools as plants go dormant in winter. But he was right when he said there are many variables that effect the climate and one is not human kind as the main forcer, but we create pollution for sure. He forgets to mention that rain usually clears dust and pollution from our cities, temporarily. Cleverly constructed argument on the side of AGW.

I like the rule which Forbes used to have for evaluating mutual funds. Grade them for performance in the up part of the cycle AND in the down part of the cycle, at least 2 of each if possible. It’s too easy to get stuck in one direction or the other.

Attempting to model anything where the physics in largely unknown, is a joke. All you have is curve fitting. Such ‘models’ have zero predictive power.
Even modelling simple systems such as fluid flow in a pipe is very difficult: “The Navier–Stokes equations are also of great interest in a purely mathematical sense. Somewhat surprisingly, given their wide range of practical uses, it has not yet been proven that in three dimensions solutions always exist (existence), or that if they do exist, then they do not contain any singularity. “

henry says
The climate is changing only because of natural reasons.
It is God who made it so.

jeffalberts says
Actually THERE’S the #1 stupid skeptic argument.

henry says
5 years ago I was definitely an Al Gore man, thinking the (climate) science was settled.
Then I ended up one day here at WUWT, reading this. I remember printing it out.https://wattsupwiththat.com/2009/12/09/hockey-stick-observed-in-noaa-ice-core-data/
From then onward I became a skeptic.Maybe take some time and read that post? It shows that there is natural variability over time..
My own subsequent investigations confirmed that we are not globally warming anymore. We are globally cooling naturally, and it will last for at least another 30 years or so.
This is somewhat worrying (to me), as (I think) it may cause famine in the future.
There is however some AGW, noted by me, but it is due to man wanting more trees and more lawns and more crops. This traps some heat. We donot know exactly how much. I doubt if it is a lot, as my figures from 1974 or so shows, But, in the final analysis, that again is due to life itself, and that is nature, and that is natural.
If you believe in God, you would assign natural variability as part of His intelligent design.
If you don’t, that you would assign the change in weather as due to nature or due to natural reasons.

“For example, I analyzed the tropical atmospheric temperature change in 102 of the latest climate-model simulations covering the past 35 years. The temperature of this region is a key target variable because it is tied directly to the response to extra greenhouse gases in models. If greenhouse gases are warming the Earth, this is the first place to look.

All 102 model runs overshot the actual temperature change on average by a factor of three. Not only does this tell us we don’t have a good grasp on the way climate varies, but the fact that all simulations overcooked the atmosphere means there is probably a warm bias built into the basic theory — the same theory we’ve been told is “settled science.”’

Streetcred writes “Have noticed over time that the BoM forecasts for Brisbane (Aust.) mostly run a degree-C or so hot.”

Perhaps we have different expectations. If they predict 15C and its 14C a few days in advance then that’s pretty good going IMO. But its actually the “features” of the weather I think they do well with. If they say showers in the afternoon in a couple of days and there ARE showers in the afternoon then that’s a good prediction in my book. Of course I’m in Tassie where weather varies considerably. We can get all 4 seasons in an afternoon so the fact they can see them coming is impressive IMO.

Lets just say you have a “method” that predicts whether it will rain on any given afternoon. Suppose the naive guess is “the same as yesterday afternoon” and say the naive guess works 25% of the time. And lets suppose the skilful “method” works 26% of the time.

So the method is skilful, but is it useful? Well you might on average pick a rainy afternoon once a year better than the naive guess. I dont think I’d be planning my BBQs on that kind of information.

When I want to go looking at pretty images, I can open a modern gaming program that shows some skill.
When I want to get into global warming science, I’m still looking, after nearly a decade, for THE definitive paper that gives a quantified, high confidence, replicated relationship between the temperature of the lower air and the concentration of CO2 in it.
Having some ‘expert’ state baldly that it is known and solid is not science. Proof, please, Gavin, give us the seminal paper that works, or just be quiet

I wonder about Gavin’s thoughts about the leaked UAE programmer’s notes, Harry Read_Me Very funny and also very sad. Even to a non-programmer such as myself, it seemed apparent no one except the programmer cared a whit about the model or the data itself, much of which was incompatible to the model. The outcome was pre-ordained.

Was that an example of Gavin’s skilled model?

And I wonder what has happened since? Has anyone untangled the code, found and reconciled all the data? ….Lady in Red

It is fascinating that the author of the quoted introduction selected “mesmerizing” to describe the TED talk, by the way:
“mes·mer·ize (mĕz′mə-rīz′, mĕs′-)
tr.v. mes·mer·ized, mes·mer·iz·ing, mes·mer·iz·es
1. To spellbind; enthrall: “He could mesmerize an audience by the sheer force of his presence” (Justin Kaplan).
2. To hypnotize.”
Mesmerize has little to do with facts and much to do with illusion, sucking ’em in, magical performance and hypnotic suggestion.
Dr. Schmidt’s strategy seems to be a sophisticated version of the same one used by the tailor in “The Emperor’s New Clothes”.
We must be mesmerized by the many fine details of his amazing models to finally see the whole magnificent vision he is selling us.

Tom you are right, it was a cleverly constructed lecture. Some things he said were correct, but the conclusion mentioned increased CO2 and that’s when it lost me. There are many variables in weather predictions, and a few .Cs increase will not be terrible.
Australia on the Northern Tablelands are recording some of the lowest temps ever recorded and we are only mid Autumn? Snow in parts Inverell. But non in Armidale just a bit of sleet yesterday and one or two snow flakes for a few minutes.

I shook my head immediately when I read Mosher’s comment. I would suspect that most “skeptics”, if asked about future climate in 1938, would immediately ask what was gong to happen with the sun. If strong solar cycles were likely then the “skeptics” would have concluded the climate would warm. Seems like they would have been right.

The eminent scholars of the climate modeling community constantly update (tweak) their models with fresh data and coefficients to adjust an ensembled output to match adjusted data. Then they smugly point out how well the fresh output blodge matches history. They will never understand how corrupt and stupid this scheme is. It’s not science, it’s nonsense.

Climate modeler Gavin Schmidt is defensive about CGMs in his TED talk.

Research money has gotten significantly scarcer in recent years and climate modeling has been very expensive in prior years.

Given that Schmidt is a salesman for his climate modeling profession, my assessment of his GCM sales advertisement (sales pitch) in his TED talk is that he was not effective enough to make Joe Public give more cash.

Climate modeling was unjustifiably and myopically prioritized by the IPCC process, so it was overfunded. Models have a much reduced role in the current developing mix of climate research / assessment, but they still have a role of a very reduced and limited scope.

@Henry, I agree that we are most likely already in a cooling period. It may take a few more years to say for sure though, at least without a claim of cherry-picking from the Warmists. The beauty of the halt (not pause) is that there is no cherry-picking since the period goes from today backwards in time.

I don’t know about some of you, maybe all, but when I studied archaeology and palaeoanthropology at UNE (Oz) we studied the evolution of humans. When Al Gore got the Nobel Prize I nearly spewed. But it is very interesting that when there is a extreme climate change, i.e., from glacial, interglacial, humans have adapted. During the MIA the wine industry slumped in UK and some parts of Europe. They changed the wine presses into the early printing presses, and we got books. For those who could afford them and could read. And that goes back millennium. The presents as changes in technology too and the type of tools they made.It affects body mass too. Like the Neanderthals were thick and stocky, like Inuits to combat colder weather. Yet Africans were more slender and lithe.

There’s a big difference: The astronomers’ epicycles worked. That’s because the motions of celestial objects are very regular and therefore can be matched by introducing epicycles into the models. The same is not true of climate.

The epicycles were not introduced for the purpose of protecting anyone’s status. There was nothing to protect them against.

Moreover, AFAIK, no one ever claimed that the epicycles were real. It’s possible I’m wrong about that, but the reason the Church was initially confused about Galileo was that they didn’t think he was claiming that heliocentrism was true as matter of fact.